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Record W4416231272 · doi:10.1021/acs.cgd.5c01298

Oriented Aggregation of Silicalite-1 Subcrystals into MFI Zeolite Crystals

2025· article· en· W4416231272 on OpenAlexaff
Xiaoge Wang, Ke Du, He Li, Xiaofan Cao, Yanting Li, Yahong Zhang, Jing Ju

Bibliographic record

VenueCrystal Growth & Design · 2025
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsZeolitePorosityNanoparticleAqueous solutionFabricationHydrolysisCrystal (programming language)Hydroxide

Abstract

fetched live from OpenAlex

Precursor nanoparticles that form spontaneously on hydrolysis of silica source in aqueous solutions of tetrapropylammonium (TPA) hydroxide evolve to (TPA)- silicalite-1, a molecular-sieve crystal that serves as a model for the self-assembly of porous inorganic materials in the presence of organic structure-directing agents. The structure and role of these nanoparticles are of practical significance for the fabrication of 3-dimensional (3D) ordered porous materials and molecular-sieve films, but still remain elusive. Here we show experimental findings of nanoparticle and crystal evolution by controllable manipulation of silicalite-1 synthesis. We have investigated detailed structural features of MFI precursors, which involves precise temperature control during synthesis, fine purification of 6–10 nm silicalite-1 subcrystals (SCs) as starting materials, and subsequent compression via an ice-templating method. SCs aggregate into MFI crystals with unidirectional orientation─indicating that SCs possess at least partial MFI structure and a slab-like morphology. This synthetic route is not only facile and environmentally friendly but also highly reproducible. We believe this method holds great promise for advancing the application of membrane-based separation processes in the natural gas industry and organic liquid separation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.244
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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